from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 13.0 | 27.929018 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 28.180371 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 25.288477 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 46.040990 |
| KMeans_tall | 0.0 | 1.0 | 40.003804 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 16.258772 |
| KMeans_short | 0.0 | 0.0 | 17.791250 |
| daal4py_KMeans_short | 0.0 | 0.0 | 8.693973 |
| LogisticRegression | 0.0 | 1.0 | 7.899610 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 31.369216 |
| Ridge | 0.0 | 0.0 | 25.323295 |
| daal4py_Ridge | 0.0 | 0.0 | 6.586265 |
| total | 0.0 | 30.0 | 41.440431 |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | n_jobs | n_neighbors | throughput | latency | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.133 | 0.002 | 1000000 | 1000000 | 100 | -1 | 1 | 6.029 | NaN | 0.984 | 0.977 | 0.502 | 0.008 | 0.264 | 0.006 | See | See |
| 1 | KNeighborsClassifier | predict | 25.129 | 0.130 | 1000000 | 1000 | 100 | -1 | 1 | 0.000 | 0.025 | 0.984 | 0.977 | 2.030 | 0.040 | 12.381 | 0.253 | See | See |
| 2 | KNeighborsClassifier | predict | 0.163 | 0.017 | 1000000 | 1 | 100 | -1 | 1 | 0.005 | 0.000 | 0.984 | 0.977 | 0.082 | 0.001 | 1.982 | 0.204 | See | See |
| 3 | KNeighborsClassifier | fit | 0.132 | 0.004 | 1000000 | 1000000 | 100 | -1 | 5 | 6.043 | NaN | 0.984 | 0.977 | 0.477 | 0.004 | 0.277 | 0.009 | See | See |
| 4 | KNeighborsClassifier | predict | 33.448 | 0.000 | 1000000 | 1000 | 100 | -1 | 5 | 0.000 | 0.033 | 0.984 | 0.977 | 2.044 | 0.052 | 16.365 | 0.418 | See | See |
| 5 | KNeighborsClassifier | predict | 0.169 | 0.016 | 1000000 | 1 | 100 | -1 | 5 | 0.005 | 0.000 | 0.984 | 0.977 | 0.086 | 0.006 | 1.953 | 0.230 | See | See |
| 6 | KNeighborsClassifier | fit | 0.125 | 0.000 | 1000000 | 1000000 | 100 | -1 | 100 | 6.424 | NaN | 0.984 | 0.977 | 0.478 | 0.002 | 0.260 | 0.001 | See | See |
| 7 | KNeighborsClassifier | predict | 33.407 | 0.000 | 1000000 | 1000 | 100 | -1 | 100 | 0.000 | 0.033 | 0.984 | 0.977 | 2.091 | 0.031 | 15.974 | 0.238 | See | See |
| 8 | KNeighborsClassifier | predict | 0.165 | 0.018 | 1000000 | 1 | 100 | -1 | 100 | 0.005 | 0.000 | 0.984 | 0.977 | 0.083 | 0.000 | 1.989 | 0.211 | See | See |
| 9 | KNeighborsClassifier | fit | 0.125 | 0.001 | 1000000 | 1000000 | 100 | 1 | 1 | 6.413 | NaN | 0.984 | 0.977 | 0.479 | 0.003 | 0.261 | 0.002 | See | See |
| 10 | KNeighborsClassifier | predict | 13.298 | 0.016 | 1000000 | 1000 | 100 | 1 | 1 | 0.000 | 0.013 | 0.984 | 0.977 | 2.017 | 0.021 | 6.595 | 0.068 | See | See |
| 11 | KNeighborsClassifier | predict | 0.181 | 0.004 | 1000000 | 1 | 100 | 1 | 1 | 0.004 | 0.000 | 0.984 | 0.977 | 0.083 | 0.001 | 2.186 | 0.045 | See | See |
| 12 | KNeighborsClassifier | fit | 0.125 | 0.000 | 1000000 | 1000000 | 100 | 1 | 5 | 6.389 | NaN | 0.984 | 0.977 | 0.478 | 0.004 | 0.262 | 0.002 | See | See |
| 13 | KNeighborsClassifier | predict | 22.153 | 0.035 | 1000000 | 1000 | 100 | 1 | 5 | 0.000 | 0.022 | 0.984 | 0.977 | 2.051 | 0.021 | 10.803 | 0.111 | See | See |
| 14 | KNeighborsClassifier | predict | 0.178 | 0.002 | 1000000 | 1 | 100 | 1 | 5 | 0.005 | 0.000 | 0.984 | 0.977 | 0.083 | 0.000 | 2.148 | 0.026 | See | See |
| 15 | KNeighborsClassifier | fit | 0.136 | 0.003 | 1000000 | 1000000 | 100 | 1 | 100 | 5.866 | NaN | 0.984 | 0.977 | 0.483 | 0.004 | 0.283 | 0.006 | See | See |
| 16 | KNeighborsClassifier | predict | 22.198 | 0.003 | 1000000 | 1000 | 100 | 1 | 100 | 0.000 | 0.022 | 0.984 | 0.977 | 2.091 | 0.018 | 10.618 | 0.092 | See | See |
| 17 | KNeighborsClassifier | predict | 0.176 | 0.002 | 1000000 | 1 | 100 | 1 | 100 | 0.005 | 0.000 | 0.984 | 0.977 | 0.085 | 0.001 | 2.080 | 0.041 | See | See |
| 18 | KNeighborsClassifier | fit | 0.061 | 0.000 | 1000000 | 1000000 | 2 | -1 | 1 | 0.264 | NaN | 0.984 | 0.977 | 0.108 | 0.003 | 0.561 | 0.016 | See | See |
| 19 | KNeighborsClassifier | predict | 21.669 | 0.020 | 1000000 | 1000 | 2 | -1 | 1 | 0.000 | 0.022 | 0.984 | 0.977 | 0.318 | 0.011 | 68.094 | 2.339 | See | See |
| 20 | KNeighborsClassifier | predict | 0.020 | 0.001 | 1000000 | 1 | 2 | -1 | 1 | 0.001 | 0.000 | 0.984 | 0.977 | 0.007 | 0.001 | 3.012 | 0.473 | See | See |
| 21 | KNeighborsClassifier | fit | 0.061 | 0.000 | 1000000 | 1000000 | 2 | -1 | 5 | 0.261 | NaN | 0.984 | 0.977 | 0.108 | 0.003 | 0.569 | 0.017 | See | See |
| 22 | KNeighborsClassifier | predict | 31.777 | 0.000 | 1000000 | 1000 | 2 | -1 | 5 | 0.000 | 0.032 | 0.984 | 0.977 | 0.317 | 0.005 | 100.400 | 1.433 | See | See |
| 23 | KNeighborsClassifier | predict | 0.028 | 0.001 | 1000000 | 1 | 2 | -1 | 5 | 0.001 | 0.000 | 0.984 | 0.977 | 0.006 | 0.001 | 4.492 | 0.776 | See | See |
| 24 | KNeighborsClassifier | fit | 0.061 | 0.001 | 1000000 | 1000000 | 2 | -1 | 100 | 0.264 | NaN | 0.984 | 0.977 | 0.108 | 0.002 | 0.562 | 0.010 | See | See |
| 25 | KNeighborsClassifier | predict | 32.196 | 0.000 | 1000000 | 1000 | 2 | -1 | 100 | 0.000 | 0.032 | 0.984 | 0.977 | 0.375 | 0.004 | 85.849 | 0.995 | See | See |
| 26 | KNeighborsClassifier | predict | 0.029 | 0.002 | 1000000 | 1 | 2 | -1 | 100 | 0.001 | 0.000 | 0.984 | 0.977 | 0.008 | 0.000 | 3.789 | 0.321 | See | See |
| 27 | KNeighborsClassifier | fit | 0.064 | 0.002 | 1000000 | 1000000 | 2 | 1 | 1 | 0.251 | NaN | 0.984 | 0.977 | 0.110 | 0.003 | 0.583 | 0.025 | See | See |
| 28 | KNeighborsClassifier | predict | 10.397 | 0.216 | 1000000 | 1000 | 2 | 1 | 1 | 0.000 | 0.010 | 0.984 | 0.977 | 0.318 | 0.008 | 32.732 | 1.066 | See | See |
| 29 | KNeighborsClassifier | predict | 0.015 | 0.000 | 1000000 | 1 | 2 | 1 | 1 | 0.001 | 0.000 | 0.984 | 0.977 | 0.006 | 0.001 | 2.380 | 0.287 | See | See |
| 30 | KNeighborsClassifier | fit | 0.061 | 0.000 | 1000000 | 1000000 | 2 | 1 | 5 | 0.260 | NaN | 0.984 | 0.977 | 0.108 | 0.004 | 0.567 | 0.019 | See | See |
| 31 | KNeighborsClassifier | predict | 20.387 | 0.006 | 1000000 | 1000 | 2 | 1 | 5 | 0.000 | 0.020 | 0.984 | 0.977 | 0.318 | 0.005 | 64.108 | 1.099 | See | See |
| 32 | KNeighborsClassifier | predict | 0.023 | 0.001 | 1000000 | 1 | 2 | 1 | 5 | 0.001 | 0.000 | 0.984 | 0.977 | 0.006 | 0.000 | 3.645 | 0.293 | See | See |
| 33 | KNeighborsClassifier | fit | 0.060 | 0.000 | 1000000 | 1000000 | 2 | 1 | 100 | 0.266 | NaN | 0.984 | 0.977 | 0.107 | 0.002 | 0.564 | 0.011 | See | See |
| 34 | KNeighborsClassifier | predict | 20.495 | 0.040 | 1000000 | 1000 | 2 | 1 | 100 | 0.000 | 0.020 | 0.984 | 0.977 | 0.389 | 0.026 | 52.703 | 3.459 | See | See |
| 35 | KNeighborsClassifier | predict | 0.023 | 0.001 | 1000000 | 1 | 2 | 1 | 100 | 0.001 | 0.000 | 0.984 | 0.977 | 0.006 | 0.001 | 3.528 | 0.580 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | n_jobs | n_neighbors | throughput | latency | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.152 | 0.036 | 1000000 | 1000000 | 10 | -1 | 1 | 0.025 | NaN | 0.983 | 0.99 | 0.751 | 0.022 | 4.196 | 0.131 | See | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.476 | 0.014 | 1000000 | 1000 | 10 | -1 | 1 | 0.000 | 0.000 | 0.983 | 0.99 | 0.106 | 0.007 | 4.482 | 0.326 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.005 | 0.002 | 1000000 | 1 | 10 | -1 | 1 | 0.016 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 9.692 | 5.604 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.209 | 0.103 | 1000000 | 1000000 | 10 | -1 | 5 | 0.025 | NaN | 0.983 | 0.99 | 0.767 | 0.014 | 4.185 | 0.155 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.800 | 0.014 | 1000000 | 1000 | 10 | -1 | 5 | 0.000 | 0.001 | 0.983 | 0.99 | 0.189 | 0.006 | 4.223 | 0.154 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.005 | 0.006 | 1000000 | 1 | 10 | -1 | 5 | 0.015 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 6.422 | 7.746 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.177 | 0.040 | 1000000 | 1000000 | 10 | -1 | 100 | 0.025 | NaN | 0.983 | 0.99 | 0.732 | 0.011 | 4.337 | 0.085 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 2.762 | 0.052 | 1000000 | 1000 | 10 | -1 | 100 | 0.000 | 0.003 | 0.983 | 0.99 | 0.571 | 0.014 | 4.841 | 0.150 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | -1 | 100 | 0.018 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 3.195 | 1.160 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.126 | 0.076 | 1000000 | 1000000 | 10 | 1 | 1 | 0.026 | NaN | 0.983 | 0.99 | 0.751 | 0.007 | 4.165 | 0.107 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.722 | 0.004 | 1000000 | 1000 | 10 | 1 | 1 | 0.000 | 0.001 | 0.983 | 0.99 | 0.102 | 0.001 | 7.076 | 0.105 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | 1 | 1 | 0.099 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 1.621 | 0.654 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.035 | 0.017 | 1000000 | 1000000 | 10 | 1 | 5 | 0.026 | NaN | 0.983 | 0.99 | 0.723 | 0.008 | 4.196 | 0.051 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1.428 | 0.017 | 1000000 | 1000 | 10 | 1 | 5 | 0.000 | 0.001 | 0.983 | 0.99 | 0.192 | 0.006 | 7.448 | 0.235 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | 1 | 5 | 0.067 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 1.497 | 0.668 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.048 | 0.018 | 1000000 | 1000000 | 10 | 1 | 100 | 0.026 | NaN | 0.983 | 0.99 | 0.756 | 0.019 | 4.029 | 0.101 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 4.598 | 0.016 | 1000000 | 1000 | 10 | 1 | 100 | 0.000 | 0.005 | 0.983 | 0.99 | 0.591 | 0.020 | 7.785 | 0.265 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 10 | 1 | 100 | 0.033 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 1.746 | 0.719 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 0.835 | 0.004 | 1000000 | 1000000 | 2 | -1 | 1 | 0.019 | NaN | 0.983 | 0.99 | 0.497 | 0.005 | 1.678 | 0.019 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.029 | 0.003 | 1000000 | 1000 | 2 | -1 | 1 | 0.001 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 37.015 | 10.633 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | -1 | 1 | 0.006 | 0.000 | 0.983 | 0.99 | 0.000 | 0.000 | 22.219 | 14.887 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 0.850 | 0.020 | 1000000 | 1000000 | 2 | -1 | 5 | 0.019 | NaN | 0.983 | 0.99 | 0.492 | 0.002 | 1.728 | 0.042 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.031 | 0.001 | 1000000 | 1000 | 2 | -1 | 5 | 0.001 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 21.860 | 7.386 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | -1 | 5 | 0.006 | 0.000 | 0.983 | 0.99 | 0.000 | 0.000 | 21.245 | 15.002 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 0.836 | 0.010 | 1000000 | 1000000 | 2 | -1 | 100 | 0.019 | NaN | 0.983 | 0.99 | 0.501 | 0.011 | 1.671 | 0.042 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.051 | 0.002 | 1000000 | 1000 | 2 | -1 | 100 | 0.000 | 0.000 | 0.983 | 0.99 | 0.007 | 0.001 | 7.069 | 1.010 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | -1 | 100 | 0.006 | 0.000 | 0.983 | 0.99 | 0.000 | 0.000 | 20.146 | 12.730 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 0.834 | 0.005 | 1000000 | 1000000 | 2 | 1 | 1 | 0.019 | NaN | 0.983 | 0.99 | 0.505 | 0.009 | 1.654 | 0.032 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.026 | 0.001 | 1000000 | 1000 | 2 | 1 | 1 | 0.001 | 0.000 | 0.983 | 0.99 | 0.001 | 0.000 | 29.427 | 8.344 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | 1 | 1 | 0.023 | 0.000 | 0.983 | 0.99 | 0.000 | 0.000 | 5.965 | 4.278 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 0.838 | 0.004 | 1000000 | 1000000 | 2 | 1 | 5 | 0.019 | NaN | 0.983 | 0.99 | 0.517 | 0.033 | 1.622 | 0.102 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.028 | 0.001 | 1000000 | 1000 | 2 | 1 | 5 | 0.001 | 0.000 | 0.983 | 0.99 | 0.002 | 0.000 | 17.990 | 5.609 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | 1 | 5 | 0.024 | 0.000 | 0.983 | 0.99 | 0.000 | 0.000 | 5.724 | 4.130 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 0.840 | 0.003 | 1000000 | 1000000 | 2 | 1 | 100 | 0.019 | NaN | 0.983 | 0.99 | 0.502 | 0.013 | 1.674 | 0.043 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.055 | 0.001 | 1000000 | 1000 | 2 | 1 | 100 | 0.000 | 0.000 | 0.983 | 0.99 | 0.007 | 0.001 | 7.382 | 1.115 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | 1 | 100 | 0.022 | 0.000 | 0.983 | 0.99 | 0.000 | 0.000 | 5.406 | 3.594 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | init | n_iter_sklearn | throughput | latency | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.617 | 0.013 | 1000000 | 1000000 | 2 | k-means++ | 30 | 0.777 | NaN | 0.002 | 30 | 0.002 | 0.502 | 0.036 | 1.229 | 0.092 | See | See |
| 1 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 2 | k-means++ | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 9.072 | 5.148 | See | See |
| 2 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | k-means++ | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 11.219 | 7.022 | See | See |
| 3 | KMeans_tall | fit | 0.564 | 0.006 | 1000000 | 1000000 | 2 | random | 30 | 0.851 | NaN | 0.002 | 30 | 0.002 | 0.461 | 0.041 | 1.225 | 0.111 | See | See |
| 4 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 2 | random | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 8.219 | 4.358 | See | See |
| 5 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | random | 30 | 0.011 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 10.556 | 5.999 | See | See |
| 6 | KMeans_tall | fit | 6.453 | 0.119 | 1000000 | 1000000 | 100 | k-means++ | 30 | 3.719 | NaN | 0.002 | 30 | 0.002 | 2.987 | 0.040 | 2.161 | 0.049 | See | See |
| 7 | KMeans_tall | predict | 0.002 | 0.001 | 1000000 | 1000 | 100 | k-means++ | 30 | 0.371 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 7.645 | 3.539 | See | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 100 | k-means++ | 30 | 0.558 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 10.299 | 5.823 | See | See |
| 9 | KMeans_tall | fit | 6.041 | 0.099 | 1000000 | 1000000 | 100 | random | 30 | 3.973 | NaN | 0.002 | 30 | 0.002 | 2.774 | 0.020 | 2.177 | 0.039 | See | See |
| 10 | KMeans_tall | predict | 0.002 | 0.000 | 1000000 | 1000 | 100 | random | 30 | 0.439 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 6.436 | 2.401 | See | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 100 | random | 30 | 0.557 | 0.0 | 0.002 | 30 | 0.002 | 0.000 | 0.000 | 9.781 | 5.257 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 20 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | init | n_iter_sklearn | throughput | latency | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.263 | 0.003 | 10000 | 10000 | 2 | k-means++ | 20 | 0.012 | NaN | 0.262 | 20 | 0.298 | 0.102 | 0.002 | 2.579 | 0.068 | See | See |
| 1 | KMeans_short | predict | 0.002 | 0.001 | 10000 | 1000 | 2 | k-means++ | 20 | 0.007 | 0.0 | 0.262 | 20 | 0.298 | 0.001 | 0.000 | 3.005 | 1.576 | See | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 2 | k-means++ | 20 | 0.011 | 0.0 | 0.262 | 20 | 0.298 | 0.000 | 0.000 | 9.669 | 5.227 | See | See |
| 3 | KMeans_short | fit | 0.090 | 0.004 | 10000 | 10000 | 2 | random | 20 | 0.036 | NaN | 0.262 | 20 | 0.298 | 0.037 | 0.005 | 2.454 | 0.351 | See | See |
| 4 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1000 | 2 | random | 20 | 0.008 | 0.0 | 0.262 | 20 | 0.298 | 0.001 | 0.000 | 2.647 | 0.603 | See | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 2 | random | 20 | 0.011 | 0.0 | 0.262 | 20 | 0.298 | 0.000 | 0.000 | 9.426 | 6.779 | See | See |
| 6 | KMeans_short | fit | 0.678 | 0.011 | 10000 | 10000 | 100 | k-means++ | 20 | 0.236 | NaN | 0.262 | 20 | 0.298 | 0.369 | 0.009 | 1.835 | 0.052 | See | See |
| 7 | KMeans_short | predict | 0.003 | 0.000 | 10000 | 1000 | 100 | k-means++ | 20 | 0.278 | 0.0 | 0.262 | 20 | 0.298 | 0.001 | 0.000 | 1.969 | 0.382 | See | See |
| 8 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 100 | k-means++ | 20 | 0.511 | 0.0 | 0.262 | 20 | 0.298 | 0.000 | 0.000 | 8.618 | 4.057 | See | See |
| 9 | KMeans_short | fit | 0.233 | 0.009 | 10000 | 10000 | 100 | random | 20 | 0.685 | NaN | 0.262 | 20 | 0.298 | 0.149 | 0.003 | 1.566 | 0.068 | See | See |
| 10 | KMeans_short | predict | 0.003 | 0.000 | 10000 | 1000 | 100 | random | 20 | 0.283 | 0.0 | 0.262 | 20 | 0.298 | 0.001 | 0.000 | 2.030 | 0.396 | See | See |
| 11 | KMeans_short | predict | 0.002 | 0.000 | 10000 | 1 | 100 | random | 20 | 0.513 | 0.0 | 0.262 | 20 | 0.298 | 0.000 | 0.000 | 8.284 | 4.469 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | class_weight | l1_ratio | n_jobs | random_state | n_iter | throughput | latency | accuracy_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 12.374 | 0.301 | 1000000 | 1000000 | 100 | NaN | NaN | NaN | NaN | [20] | [-0.09535207] | NaN | 0.25 | 1.945 | 0.026 | 6.363 | 0.176 | See | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | NaN | NaN | NaN | NaN | [20] | 2.5134737900215343 | 0.0 | 0.25 | 0.000 | 0.000 | 0.813 | 0.342 | See | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | NaN | NaN | NaN | NaN | [20] | 10.878270785963549 | 0.0 | 0.25 | 0.000 | 0.000 | 0.374 | 0.308 | See | See |
| 3 | LogisticRegression | fit | 0.793 | 0.008 | 1000 | 1000 | 10000 | NaN | NaN | NaN | NaN | [28] | [-2.5911627] | NaN | 0.25 | 0.721 | 0.031 | 1.100 | 0.049 | See | See |
| 4 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | NaN | NaN | NaN | NaN | [28] | 4.571599157145027 | 0.0 | 0.25 | 0.003 | 0.000 | 0.545 | 0.090 | See | See |
| 5 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | NaN | NaN | NaN | NaN | [28] | 73.30599020375392 | 0.0 | 0.25 | 0.001 | 0.000 | 0.144 | 0.079 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | deprecated |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | max_iter | random_state | throughput | latency | r2_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.187 | 0.002 | 1000 | 1000 | 10000 | NaN | NaN | 0.428 | NaN | 1.0 | 0.173 | 0.002 | 1.083 | 0.014 | See | See |
| 1 | Ridge | predict | 0.010 | 0.000 | 1000 | 1000 | 10000 | NaN | NaN | 8.072 | 0.0 | 1.0 | 0.017 | 0.000 | 0.588 | 0.018 | See | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | NaN | NaN | 969.565 | 0.0 | 1.0 | 0.000 | 0.000 | 0.662 | 0.614 | See | See |
| 3 | Ridge | fit | 1.168 | 0.049 | 1000000 | 1000000 | 100 | NaN | NaN | 0.685 | NaN | 1.0 | 0.243 | 0.006 | 4.815 | 0.233 | See | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | NaN | NaN | 4.415 | 0.0 | 1.0 | 0.000 | 0.000 | 0.709 | 0.386 | See | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | NaN | NaN | 12.019 | 0.0 | 1.0 | 0.000 | 0.000 | 0.628 | 0.566 | See | See |
{
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"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1047-azure-x86_64-with-glibc2.10"
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"dependencies_info": {
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{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/python3.8/site-packages/scikit_learn.libs/libgomp-f7e03b3e.so.1.0.0",
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